scholarly journals Regulation ofecmFgene expression and genetic hierarchy among STATa, CudA, and MybC on several prestalk A-specific gene expressions inDictyostelium

2016 ◽  
Vol 58 (4) ◽  
pp. 383-399 ◽  
Author(s):  
Yukika Saga ◽  
Tomoka Inamura ◽  
Nao Shimada ◽  
Takefumi Kawata
Keyword(s):  
Specific Gene ◽  
Gene Expressions ◽  
Genetic Hierarchy

scholarly journals Coculture with hiPS-derived intestinal cells enhanced human hepatocyte functions in a pneumatic-pressure-driven two-organ microphysiological system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marie Shinohara ◽  
Hiroshi Arakawa ◽  
Yuuichi Oda ◽  
Nobuaki Shiraki ◽  
Shinji Sugiura ◽  
...  
Keyword(s):  
Normal Cell ◽  
Human Hepatocytes ◽  
New Drugs ◽  
Intestinal Cells ◽  
Specific Gene ◽  
Gene Expressions ◽  
Normal Cells ◽  
Pneumatic Pressure ◽  
Pressure Driven

AbstractExamining intestine–liver interactions is important for achieving the desired physiological drug absorption and metabolism response in in vitro drug tests. Multi-organ microphysiological systems (MPSs) constitute promising tools for evaluating inter-organ interactions in vitro. For coculture on MPSs, normal cells are challenging to use because they require complex maintenance and careful handling. Herein, we demonstrated the potential of coculturing normal cells on MPSs in the evaluation of intestine–liver interactions. To this end, we cocultured human-induced pluripotent stem cell-derived intestinal cells and fresh human hepatocytes which were isolated from PXB mice with medium circulation in a pneumatic-pressure-driven MPS with pipette-friendly liquid-handling options. The cytochrome activity, albumin production, and liver-specific gene expressions in human hepatocytes freshly isolated from a PXB mouse were significantly upregulated via coculture with hiPS-intestinal cells. Our normal cell coculture shows the effects of the interactions between the intestine and liver that may occur in vivo. This study is the first to demonstrate the coculturing of hiPS-intestinal cells and fresh human hepatocytes on an MPS for examining pure inter-organ interactions. Normal-cell coculture using the multi-organ MPS could be pursued to explore unknown physiological mechanisms of inter-organ interactions in vitro and investigate the physiological response of new drugs.

scholarly journals Dysregulation of MS risk genes and pathways at distinct stages of disease

2017 ◽  
Vol 4 (3) ◽  
pp. e337 ◽  
Author(s):  
Sundararajan Srinivasan ◽  
Marco Di Dario ◽  
Alessandra Russo ◽  
Ramesh Menon ◽  
Elena Brini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Gene List ◽  
Literature Mining ◽  
Specific Gene ◽  
Healthy Population ◽  
Gene Expressions ◽  
Altered Expression ◽  
Risk Genes

Objective:To perform systematic transcriptomic analysis of multiple sclerosis (MS) risk genes in peripheral blood mononuclear cells (PBMCs) of subjects with distinct MS stages and describe the pathways characterized by dysregulated gene expressions.Methods:We monitored gene expression levels in PBMCs from 3 independent cohorts for a total of 297 cases (including clinically isolated syndromes (CIS), relapsing-remitting MS, primary and secondary progressive MS) and 96 healthy controls by distinct microarray platforms and quantitative PCR. Differential expression and pathway analyses for distinct MS stages were defined and validated by literature mining.Results:Genes located in the vicinity of MS risk variants displayed altered expression in peripheral blood at distinct stages of MS compared with the healthy population. The frequency of dysregulation was significantly higher than expected in CIS and progressive forms of MS. Pathway analysis for each MS stage–specific gene list showed that dysregulated genes contributed to pathogenic processes with scientific evidence in MS.Conclusions:Systematic gene expression analysis in PBMCs highlighted selective dysregulation of MS susceptibility genes playing a role in novel and well-known pathogenic pathways.

scholarly journals Effect of local anesthetics on viability and differentiation of various adult stem/progenitor cells

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Young Hoon Kim ◽  
Ga Young Park ◽  
Nechama Rabinovitch ◽  
Solaiman Tarafder ◽  
Chang H. Lee
Keyword(s):  
Progenitor Cells ◽  
Local Anesthetics ◽  
Adipogenic Differentiation ◽  
Cell Types ◽  
Dose Effect ◽  
Specific Gene ◽  
Gene Expressions ◽  
Differentiation Capacity ◽  
Matrix Deposition ◽  
Lineage Differentiation

Abstract Background Local anesthetics (LAs) are widely used to control pain during various clinical treatments. One of the side effects of LAs, cytotoxicity, has been investigated in various cells including stem/progenitor cells. However, our understanding of the effects of LAs on the differentiation capacity of stem/progenitor cells still remains limited. Therefore, a comparative study was conducted to investigate the effects of multiple LAs on viability and multi-lineage differentiation of stem/progenitor cells that originated from various adult tissues. Method Multiple types of stem/progenitor cells, including bone marrow mesenchymal stem/progenitor cells (MSCs), dental pulp stem/progenitor cells (DPSCs), periodontal ligament stem/progenitor cells (PDLSCs), and tendon-derived stem/progenitor cells, were either obtained from a commercial provider or isolated from adult human donors. Lidocaine (LD) and bupivacaine (BP) at various doses (1×, 0.75×, 0.5×, and 0.25× of each physiological dose) were applied to the different stem/progenitor cells for an hour, followed by induction of fibrogenic, chondrogenic, osteogenic, and adipogenic differentiation. Live/dead and MTT assays were performed at 24 h after the LD or BP treatment. At 2 weeks, qRT-PCR was conducted to evaluate the gene expressions associated with differentiation. After 4 weeks, multiple biochemical staining was performed to evaluate matrix deposition. Results At 24 h after LD or BP treatment, 1× and 0.75× physiological doses of LD and BP showed significant cytotoxicity in all the tested adult stem/progenitor cells. At 0.5×, BP resulted in higher viability than the same dose LD, with variance between cell types. Overall, the gene expressions associated with fibrogenic, chondrogenic, osteogenic, and adipogenic differentiation were attenuated in LD or BP pre-treated stem/progenitor cells, with notable dose-effect and dependence on types. In contrast, certain doses of LD and/or BP were found to increase specific gene expression, depending on the cell types. Conclusion Our data suggest that LAs such as LD and BP affect not only the viability but also the differentiation capacity of adult stem/progenitor cells from various anatomical sites. This study sheds light on stem cell applications for tissue regeneration in which isolation and transplantation of stem cells frequently involve LA administration.

scholarly journals Global Transcriptomic Analysis of the Interactions between Phage φAbp1 and Extensively Drug-ResistantAcinetobacter baumannii

mSystems ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Zichen Yang ◽  
Supeng Yin ◽  
Gang Li ◽  
Jing Wang ◽  
Guangtao Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bioinformatic Analysis ◽  
Virus Multiplication ◽  
Specific Gene ◽  
Drug Resistant ◽  
Gene Expressions ◽  
Content Type ◽  
Host Interactions ◽  
Resistance Factors ◽  
Extensively Drug Resistant

ABSTRACTAcinetobacter baumanniiis a growing threat, although lytic bacteriophages have been shown to effectively killA. baumannii. However, the interaction between the host and the phage has not been fully studied. We demonstrate the global profile of transcriptional changes in extensively drug-resistantA. baumanniiAB1 and the interaction with phage φAbp1 through RNA sequencing (RNA-seq) and bioinformatic analysis. Only 15.6% (600/3,838) of the genes of the infected host were determined to be differentially expressed genes (DEGs), indicating that only a small part of the bacterial resources was needed for φAbp1 propagation. Contrary to previous similar studies, more upregulated rather than downregulated DEGs were detected. Specifically, φAbp1 infection caused the most extensive impact on host gene expression at 10 min, which was related to the intracellular accumulation phase of virus multiplication. Based on the gene coexpression network, a middle gene (gp34, encoding phage-associated RNA polymerase) showed a negative interaction with numerous host ribosome protein genes. In addition, the gene expression of bacterial virulence/resistance factors was proven to change significantly. This work provides new insights into the interactions of φAbp1 and its host, which contributes to the further understanding of phage therapy, and provides another reference for antibacterial agents.IMPORTANCEPrevious research has reported the transcriptomic phage-host interactions inEscherichia coliandPseudomonas aeruginosa, leading to the detailed discovery of transcriptomic regulations and predictions of specific gene functions. However, a direct relationship betweenA. baumanniiand its phage has not been previously reported, althoughA. baumanniiis becoming a rigorous drug-resistant threat. We analyzed transcriptomic changes after φAbp1 infected its host, extensively drug-resistant (XDR)A. baumanniiAB1, and found defense-like responses of the host, step-by-step control by the invader, elaborate interactions between host and phage, and elevated drug resistance gene expressions of AB1 after phage infection. These findings suggest the detailed interactions ofA. baumanniiand its phage, which may provide both encouraging suggestions for drug design and advice for the clinical use of vital phage particles.

scholarly journals Cartilage Tissue-Mimetic Pellets with Multifunctional Magnetic Hyaluronic Acid-Graft-Amphiphilic Gelatin Microcapsules for Chondrogenic Stimulation

Polymers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 785
Author(s):  
Kai-Ting Hou ◽  
Ting-Yu Liu ◽  
Min-Yu Chiang ◽  
Chun-Yu Chen ◽  
Shwu-Jen Chang ◽  
...  
Keyword(s):  
Hyaluronic Acid ◽  
Magnetic Stimulation ◽  
Early Stage ◽  
Superparamagnetic Iron Oxide ◽  
Cartilage Tissue ◽  
Specific Gene ◽  
High Cell ◽  
Gene Expressions ◽  
Articular Cartilage Defect ◽  
Specific Targeting

Articular cartilage defect is a common disorder caused by sustained mechanical stress. Owing to its nature of avascular, cartilage had less reconstruction ability so there is always a need for other repair strategies. In this study, we proposed tissue-mimetic pellets composed of chondrocytes and hyaluronic acid-graft-amphiphilic gelatin microcapsules (HA-AGMCs) to serve as biomimetic chondrocyte extracellular matrix (ECM) environments. The multifunctional HA-AGMC with specific targeting on CD44 receptors provides excellent structural stability and demonstrates high cell viability even in the center of pellets after 14 days culture. Furthermore, with superparamagnetic iron oxide nanoparticles (SPIOs) in the microcapsule shell of HA-AGMCs, it not only showed sound cell guiding ability but also induced two physical stimulations of static magnetic field(S) and magnet-derived shear stress (MF) on chondrogenic regeneration. Cartilage tissue-specific gene expressions of Col II and SOX9 were upregulated in the present of HA-AGMC in the early stage, and HA-AGMC+MF+S held the highest chondrogenic commitments throughout the study. Additionally, cartilage tissue-mimetic pellets with magnetic stimulation can stimulate chondrogenesis and sGAG synthesis.

Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations

2020 ◽  
Author(s):  
Minsik Oh ◽  
Sungjoon Park ◽  
Sun Kim ◽  
Heejoon Chae
Keyword(s):  
Machine Learning ◽  
Gene Regulation ◽  
State Of The Art ◽  
Patient Specific ◽  
Specific Gene ◽  
Omics Data ◽  
Gene Expressions ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Disease Subtype

Abstract Gene expressions are subtly regulated by quantifiable measures of genetic molecules such as interaction with other genes, methylation, mutations, transcription factor and histone modifications. Integrative analysis of multi-omics data can help scientists understand the condition or patient-specific gene regulation mechanisms. However, analysis of multi-omics data is challenging since it requires not only the analysis of multiple omics data sets but also mining complex relations among different genetic molecules by using state-of-the-art machine learning methods. In addition, analysis of multi-omics data needs quite large computing infrastructure. Moreover, interpretation of the analysis results requires collaboration among many scientists, often requiring reperforming analysis from different perspectives. Many of the aforementioned technical issues can be nicely handled when machine learning tools are deployed on the cloud. In this survey article, we first survey machine learning methods that can be used for gene regulation study, and we categorize them according to five different goals: gene regulatory subnetwork discovery, disease subtype analysis, survival analysis, clinical prediction and visualization. We also summarize the methods in terms of multi-omics input types. Then, we explain why the cloud is potentially a good solution for the analysis of multi-omics data, followed by a survey of two state-of-the-art cloud systems, Galaxy and BioVLAB. Finally, we discuss important issues when the cloud is used for the analysis of multi-omics data for the gene regulation study.

scholarly journals PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuhua Zhang ◽  
◽  
Corbin Quick ◽  
Ketian Yu ◽  
Alvaro Barbeira ◽  
...  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Specific Gene ◽  
Summary Statistics ◽  
Gene Expressions ◽  
Computational Framework ◽  
Higher Power ◽  
Causal Assumptions ◽  
Cell Type Specific ◽  
Eqtl Data

Abstract We propose a new computational framework, probabilistic transcriptome-wide association study (PTWAS), to investigate causal relationships between gene expressions and complex traits. PTWAS applies the established principles from instrumental variables analysis and takes advantage of probabilistic eQTL annotations to delineate and tackle the unique challenges arising in TWAS. PTWAS not only confers higher power than the existing methods but also provides novel functionalities to evaluate the causal assumptions and estimate tissue- or cell-type-specific gene-to-trait effects. We illustrate the power of PTWAS by analyzing the eQTL data across 49 tissues from GTEx (v8) and GWAS summary statistics from 114 complex traits.

scholarly journals Regulation of Caenorhabditis Elegans model in Alzheimer’s Disease

2020 ◽  
Vol 185 ◽  
pp. 03043
Author(s):  
Yuxuan Jing
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Caenorhabditis Elegans ◽  
Amyloid Beta ◽  
Significant Role ◽  
Tau Protein ◽  
Specific Gene ◽  
Protein Modelling ◽  
Gene Expressions ◽  
The World

Alzheimer’s disease (AD) is affecting numerous families and individuals around the world nowadays, as the exact reason is still undetermined. At this stage, developmental treatment displays a particularly significant role in relieving symptoms for the patients. Currently, the two most well-known factors that have impacts on the diagnosis of AD are the plaques and tangles formed from amyloid-beta and tau protein. Modelling for Alzheimer’s disease is essential in understanding targeted aspects of the disease, while Caenorhabditis elegans (C.elegans) was chosen as a pivotal model. C.elegans presents dramatic priorities using orthologs for the study of AD, especially in examining the formation of the deposits and the regulations of specific gene expressions that result in this abnormality. This review discusses the properties, which C.elegans shows on the study of AD, and the achievements that have been approached using this model, as well as what other models are being tested by scientists. Properties of other models, which can overwhelm C.elegans, as well as the expectations for future modelling systems on AD are examined as well.

scholarly journals Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method

Biomolecules ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1293
Author(s):  
Emili Besalú ◽  
Jesus Vicente De Julián-Ortiz
Keyword(s):  
Significant Interaction ◽  
Operating Characteristic ◽  
Specific Gene ◽  
Expression Data ◽  
Related Gene ◽  
Gene Expressions ◽  
Cancer Related Gene ◽  
Key Genes ◽  
Encoding Gene ◽  
Transcription Data

The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Receiver Operating Characteristic (AU-ROC) values of 0.95 (leukemia prediction) and 0.80–0.90 (prostate). The preferential selected descriptors here are specific gene expressions, and this is potentially useful to point to possible key genes.

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